The Applied AI team at Balyasny Asset Management is at the forefront of transforming how investment professionals interact with artificial intelligence. We've built a comprehensive suite of AI-powered tools including custom assistants with deep research capabilities connected to hundreds of tools. Now we’re developing reasoning models for finance and evolving our platform to a true collaborative AI workspace where agents function as intelligent team members.
Role Overview
We are seeking a Research Scientist or Senior Research Scientist to join our Applied AI team in building the next generation of AI-powered investment tools. You will work on cutting-edge research projects that directly impact how portfolio managers, analysts, and researchers leverage AI in their daily workflows. This role requires a strong background in machine learning, and a passion for seeing your research deployed to thousands of users in production.
What sets this opportunity apart is the unparalleled environment for advancing the frontier of human + AI performance in investing. At BAM, you’ll have access to the richest possible ecosystem: comprehensive data from every major vendor and proprietary sources, the most advanced models from across the industry, scalable compute, and exposure to a deep roster of world-class investment teams. This unique combination allows you to rigorously assess, compare, and push the boundaries of what AI can achieve alongside some of the most sophisticated human investors in the world.
The ideal candidate will have a PhD in a relevant field, a strong publication record, and a demonstrated ability to translate advanced research into practical, scalable solutions.
Key Responsibilities
- Conduct original research in machine learning, with a focus on reinforcement learning, agent architectures, and large language models
- Prototype, develop, and help deploy new ML models and algorithms that power BAM’s AI capabilities
- Collaborate with engineers to integrate research outputs into production systems used by portfolio managers, analysts, and researchers
- Design experiments and analyze results to evaluate the effectiveness of new models and approaches
- Work closely with end-users to understand their needs and ensure research is aligned with practical, high-impact applications
- Contribute to the broader research community through publications, presentations, and open-source contributions as appropriate
- Mentor junior researchers and contribute to technical direction and strategy
- Participate in the full research lifecycle from ideation and literature review through deployment and monitoring
Minimum Qualifications
- PhD in Computer Science, Machine Learning, Statistics, Applied Mathematics, or a related field
- Strong publication record in top-tier conferences (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP)
- Deep expertise in machine learning, with a focus on natural language processing (NLP), reinforcement learning (RL) or related areas
- Experience developing and evaluating ML models in Python (PyTorch)
- Demonstrated ability to translate research into practical, scalable solutions
- Strong programming skills and familiarity with modern software engineering practices
Preferred Qualifications
- Experience deploying ML models in production environments with real users
- Knowledge of financial markets and investment workflows
- Experience with cloud platforms (AWS preferred)
- Familiarity with vector databases, semantic search, or information retrieval systems
- Strong communication skills and ability to work with highly sophisticated end-users
The
Applied AI team at Balyasny Asset Management is at the forefront of
transforming how investment professionals interact with artificial
intelligence. We've built a comprehensive suite of AI-powered tools
including custom assistants with deep research capabilities connected to
hundreds of tools. Now we’re developing reasoning models for finance
and evolving our platform to a true collaborative AI workspace where
agents function as intelligent team members.
Role Overview
We
are seeking a Research Scientist or Senior Research Scientist to join
our Applied AI team in building the next generation of AI-powered
investment tools. You will work on cutting-edge research projects that
directly impact how portfolio managers, analysts, and researchers
leverage AI in their daily workflows. This role requires a strong
background in machine learning, and a passion for seeing your research
deployed to thousands of users in production.
What
sets this opportunity apart is the unparalleled environment for
advancing the frontier of human + AI performance in investing. At BAM,
you’ll have access to the richest possible ecosystem: comprehensive data
from every major vendor and proprietary sources, the most advanced
models from across the industry, scalable compute, and exposure to a
deep roster of world-class investment teams. This unique combination
allows you to rigorously assess, compare, and push the boundaries of
what AI can achieve alongside some of the most sophisticated human
investors in the world.
The
ideal candidate will have a PhD in a relevant field, a strong
publication record, and a demonstrated ability to translate advanced
research into practical, scalable solutions.
Key Responsibilities
- Conduct
original research in machine learning, with a focus on reinforcement
learning, agent architectures, and large language models
- Prototype, develop, and help deploy new ML models and algorithms that power BAM’s AI capabilities
- Collaborate
with engineers to integrate research outputs into production systems
used by portfolio managers, analysts, and researchers
- Design experiments and analyze results to evaluate the effectiveness of new models and approaches
- Work closely with end-users to understand their needs and ensure research is aligned with practical, high-impact applications
- Contribute to the broader research community through publications, presentations, and open-source contributions as appropriate
- Mentor junior researchers and contribute to technical direction and strategy
- Participate in the full research lifecycle from ideation and literature review through deployment and monitoring
Minimum Qualifications
- PhD in Computer Science, Machine Learning, Statistics, Applied Mathematics, or a related field
- Strong publication record in top-tier conferences (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP)
- Deep
expertise in machine learning, with a focus on natural language
processing (NLP), reinforcement learning (RL) or related areas
- Experience developing and evaluating ML models in Python (PyTorch)
- Demonstrated ability to translate research into practical, scalable solutions
- Strong programming skills and familiarity with modern software engineering practices
Preferred Qualifications
- Experience deploying ML models in production environments with real users
- Knowledge of financial markets and investment workflows
- Experience with cloud platforms (AWS preferred)
- Familiarity with vector databases, semantic search, or information retrieval systems
- Strong communication skills and ability to work with highly sophisticated end-users
The Applied AI team at Balyasny Asset Management is at the forefront of transforming how investment professionals interact with artificial intelligence. We've built a comprehensive suite of AI-powered tools including custom assistants with deep research capabilities connected to hundreds of tools. Now we’re developing reasoning models for finance and evolving our platform to a true collaborative AI workspace where agents function as intelligent team members.
Role Overview
We are seeking a Research Scientist or Senior Research Scientist to join our Applied AI team in building the next generation of AI-powered investment tools. You will work on cutting-edge research projects that directly impact how portfolio managers, analysts, and researchers leverage AI in their daily workflows. This role requires a strong background in machine learning, and a passion for seeing your research deployed to thousands of users in production.
What sets this opportunity apart is the unparalleled environment for advancing the frontier of human + AI performance in investing. At BAM, you’ll have access to the richest possible ecosystem: comprehensive data from every major vendor and proprietary sources, the most advanced models from across the industry, scalable compute, and exposure to a deep roster of world-class investment teams. This unique combination allows you to rigorously assess, compare, and push the boundaries of what AI can achieve alongside some of the most sophisticated human investors in the world.
The ideal candidate will have a PhD in a relevant field, a strong publication record, and a demonstrated ability to translate advanced research into practical, scalable solutions.
Key Responsibilities
Conduct original research in machine learning, with a focus on reinforcement learning, agent architectures, and large language models
Prototype, develop, and help deploy new ML models and algorithms that power BAM’s AI capabilities
Collaborate with engineers to integrate research outputs into production systems used by portfolio managers, analysts, and researchers
Design experiments and analyze results to evaluate the effectiveness of new models and approaches
Work closely with end-users to understand their needs and ensure research is aligned with practical, high-impact applications
Contribute to the broader research community through publications, presentations, and open-source contributions as appropriate
Mentor junior researchers and contribute to technical direction and strategy
Participate in the full research lifecycle from ideation and literature review through deployment and monitoring
Minimum Qualifications
PhD in Computer Science, Machine Learning, Statistics, Applied Mathematics, or a related field
Strong publication record in top-tier conferences (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP)
Deep expertise in machine learning, with a focus on natural language processing (NLP), reinforcement learning (RL) or related areas
Experience developing and evaluating ML models in Python (PyTorch)
Demonstrated ability to translate research into practical, scalable solutions
Strong programming skills and familiarity with modern software engineering practices
Preferred Qualifications
Experience deploying ML models in production environments with real users
Knowledge of financial markets and investment workflows
Experience with cloud platforms (AWS preferred)
Familiarity with vector databases, semantic search, or information retrieval systems
Strong communication skills and ability to work with highly sophisticated end-users
